A series-parallel hybrid electric vehicle (HEV) powertrain has two power sources for delivering power to the vehicle traction wheels. The first power source includes an engine and a generator mechanically coupled by a planetary gear arrangement. The second power source is an electric drive system including a battery, a motor, and the generator.
When the powertrain is operating in a driving mode that includes the first power source, the planetary arrangement, together with the engine and the generator, cooperate to effect a power delivery characteristic that is analogous to the characteristic of a conventional continuously variable transmission. This is done by controlling generator speed, the generator being connected to the sun gear of the planetary arrangement and the engine being connected to a planetary carrier. The ring gear of the planetary arrangement is connected to the wheels through torque transfer gearing and a differential-and-axle-assembly.
Because of the fixed ratio of the planetary arrangement and the variable generator speed, which achieve a decoupling of engine speed and vehicle speed, the planetary arrangement acts as a power divider that divides engine output power and distributes power to the torque transfer gearing and to the generator through separate power flow paths. The portion of the power delivered from the engine to the generator can be transmitted to the motor and then to the differential-and-axle assembly through the torque transfer gearing. Generator torque functions as a torque reaction as engine power is delivered through the planetary arrangement.
When the powertrain is operating using the second power source, the motor draws power from the battery and provides driving torque to the wheels independently of the first power source.
The two power sources can provide traction power either simultaneously or independently. However, the power sources must be integrated to work together seamlessly to meet a driver's demand for power within system power constraints while optimizing total powertrain system efficiency and performance. This requires a coordination of control of the power sources.
To this end, the powertrain includes a vehicle system controller or the like configured to control the power sources. The controller determines an engine torque and engine speed operating region to meet a driver demand for power while maintaining optimal fuel economy and optimum emissions quality under various vehicle operating conditions. The powertrain can achieve better fuel economy by the controller operating the engine in its most efficient torque and speed operating region whenever possible.
A problem is that real-world driving consists of many fast demand changes, which result in the powertrain experiencing rapid transients that adversely affect the fuel economy. In general, powertrain transient responses have more influence on ‘engine efficiency’ than ‘electrical efficiency’ in the powertrain. When the powertrain moves its operation point (torque and speed) from one point to another, there is a transient process that the engine can easily run off system-optimum settings thereby costing extra energy compared to steady-state optimum. On the other hand, it is difficult to confine the engine operation strictly along a steady-state optimal path. It not only requires more control efforts but it also causes more electrical re-circulation losses depending on driving conditions. Furthermore, it is infeasible to calculate the ‘true’ global-optimal engine torque command unless all future driving conditions are known a priori, and that underlying computation is extremely intensive. The challenge is due to the complex tradeoff between instant energy efficiency and long-term system losses.
U.S. Pat. No. 7,398,147 describes an energy management strategy (EMS) based on static optimization. Such an energy management strategy utilizes offline computation to generate optimal EMS tables that are populated with steady-state values corresponding to minimum power losses. For example, the tables may contain steady-state ‘battery power’ and ‘engine speed’ targets as two degrees of control freedom. A drawback is that an offline static optimization process cannot incorporate transient dynamics into calculation.